Software Development Engineer III

Capital Group•Irvine, CA

About The Position

As a tenured Software Development Engineer, you will design and implement distributed systems and data-intensive applications that support critical investment capabilities at Capital Group. You will architect and own major services, data workflows, and analytics-driven features that directly contribute to delivering long-term value to our investors. Where helpful, you will leverage AI tools and intelligent automation to accelerate development and improve engineering productivity. Our domain is deeply analytical and increasingly AI-enabled. As we expand our use of Generative AI and emerging AI-driven capabilities, you will help shape how intelligent services are thoughtfully integrated into our production systems. You will contribute to building scalable foundations that enable AI-powered workflows, automation, and decision support — ensuring reliability, performance, and enterprise-grade quality. You will work across backend services, cloud-native architectures, and modern data platforms to deliver pragmatic solutions to complex computational challenges. You will also help design and operationalize agentic systems (LLM-powered agents and tools) that automate workflows, assist decision-making, and safely interact with enterprise data and services. You will live by the principle: “you ship it, you own it.” From ideation through production support, you will design, build, operate, and continuously improve the systems you create. You will act as a force multiplier — mentoring engineers, influencing technical direction, and setting a high bar for craftsmanship, simplicity, and operational excellence.

Requirements

6+ years of professional software development experience in one or more modern languages such as Python, C#, Java, Go, or similar.
Designed, built, and operated distributed systems in production environments.
Cloud-first mindset, with hands-on experience building scalable services on AWS or similar platforms.
Strong data engineering fundamentals and can build scalable, reliable data products (batch and streaming) across the full lifecycle: ingestion, quality, transformation, orchestration, and serving.
Comfortable with lakehouse / warehouse patterns and governance (e.g., Delta/Parquet, catalogs/lineage, access controls), and you design for data quality, auditability, and reproducibility.
Translate investment-domain needs into technical solutions and understand the importance of accuracy, timeliness, and controls.
Build and operate agentic workflows end-to-end: tool/function design, grounding (RAG/semantic retrieval), planning/execution patterns, evaluation, monitoring, and guardrails (security, privacy, prompt-injection resistance, and safe tool use).
Interested in and motivated by the practical application of Generative AI and AI-enabled capabilities/tools in all aspects of SDLC.
Design pragmatic solutions to complex analytical problems and balance innovation with operational excellence.
Identify root causes of systemic issues and drive long-term, sustainable improvements.
Uphold disciplined engineering practices, including automated testing, CI/CD, observability, and high-quality code reviews.
Exhibit excellent verbal and written communication skills and high emotional intelligence.

Nice To Haves

Experience working with large-scale data processing frameworks (e.g., Spark) or modern data platforms (e.g., Databricks).
Strong experience with Python.
Experience with data orchestration and reliability patterns (e.g., Airflow/DBT/workflows, SLAs/SLOs, data quality checks, idempotency, backfills).
Experience designing APIs and service-oriented architectures.
Experience mentoring and technically leading other engineers.

Responsibilities

Design and implement distributed systems and data-intensive applications
Architect and own major services, data workflows, and analytics-driven features
Leverage AI tools and intelligent automation
Shape how intelligent services are integrated into production systems
Contribute to building scalable foundations for AI-powered workflows
Design and operationalize agentic systems
Design, build, operate, and continuously improve systems
Mentor engineers, influence technical direction, and set a high bar for craftsmanship